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Gemini 3.1 Pro

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Re: Gemini 3.1 Pro

#461

Post by curly6 »

Macha wrote: post #431
onlyrealcuzzo wrote: post #406

Earlier quoted context omitted.

Because Search is not agentic. Most of Gemini's users are Search converts doing extended-Search-like behaviors. Agentic workflows are a VERY small percentage of all LLM usage at the moment. As that market becomes more important, Google will pour more resources into it.

> Agentic workflows are a VERY small percentage of all LLM usage at the moment. As that market becomes more important, Google will pour more resources into it. I do wonder what percentage of revenue they are. I expect it's very outsized relative to usage (e.g. approximately nobody who is receiving them is paying for those summaries at the top of search results)

> Most agent actions on our public API are low-risk and reversible. Software engineering accounted for nearly 50% of agentic activity, but we saw emerging usage in healthcare, finance, and cybersecurity.

via Anthropic

https://www.anthropic.com/research/measuring-agent-autonomy

this doesn’t answer your question, but maybe Google is comfortable with driving traffic and dependency through their platform until they can do something like this

https://www.adweek.com/media/google-gemini-ads-2026/

Re: Gemini 3.1 Pro

#462

Post by orbital-decay »

FergusArgyll wrote: post #446
orbital-decay wrote: post #292

Earlier quoted context omitted.

It's just a summary generated by a really tiny model. I guess it also an ad-hoc way to obfuscate it, yes. In particular they're hiding prompt injections they're dynamically adding sometimes. Actual CoT is hidden and entirely different from that summary. It's not very useful for you as a user, though (neither is the summary).

They hide the CoT because they don't want competitors to train on it

Training on the CoT itself is pretty dubious since it's reward hacked to some degree (as evident from e.g. GLM-4.7 which tried pulling that with 3.0 Pro, and ended up repeating Model Armor injections without really understanding/following them). In any case they aren't trying to hide it particularly hard.

Re: Gemini 3.1 Pro

#463

Post by sunaookami »

jbellis wrote: post #274
minimaxir wrote: post #23

Price is unchanged from Gemini 3 Pro: $2/M input, $12/M output. https://ai.google.dev/gemini-api/docs/pricing Knowledge cutoff is unchanged at Jan 2025. Gemini 3.1 Pro supports "medium" thinking where Gemini 3 did not: https://ai.google.dev/gemini-api/docs/gemini-3 Compare to Opus 4.6's $5/M input, $25/M output. If Gemini 3.1 Pro does indeed have similar performance, the price difference is notable.

still no minimal reasoning in G3.1P :( (this is why Opus 4.6 is worth the price -- turning off thinking makes it 3x-5x faster but it loses only a small amount of intelligence. nobody else has figured that out yet)

Thinking is just tacked on for Anthropic's models and always has been so leaving it off actually produces better results everytime.

Re: Gemini 3.1 Pro

#464

Post by onlyrealcuzzo »

Macha wrote: post #431
onlyrealcuzzo wrote: post #406

Earlier quoted context omitted.

Because Search is not agentic. Most of Gemini's users are Search converts doing extended-Search-like behaviors. Agentic workflows are a VERY small percentage of all LLM usage at the moment. As that market becomes more important, Google will pour more resources into it.

> Agentic workflows are a VERY small percentage of all LLM usage at the moment. As that market becomes more important, Google will pour more resources into it. I do wonder what percentage of revenue they are. I expect it's very outsized relative to usage (e.g. approximately nobody who is receiving them is paying for those summaries at the top of search results)

> (e.g. approximately nobody who is receiving them is paying for those summaries at the top of search results)

Nobody is paying for Search. According to Google's earnings reports - AI Overviews is increasing overall clicks on ads and overall search volume.

Re: Gemini 3.1 Pro

#465

Post by TZubiri »

simonw wrote: post #52

Pretty great pelican: https://simonwillison.net/2026/Feb/19/gemini-31-pro/ - took over 5 minutes though, but I think that's because they're having performance teething problems on launch day.

You think they are able to see their output and iterate on it? Or is it pure token generation?

Re: Gemini 3.1 Pro

#466

Post by rjh29 »

davidguetta wrote: post #162

Implementation and Sustainability Hardware: Gemini 3 Pro was trained using Google’s Tensor Processing Units (TPUs). TPUs are specically designed to handle the massive computations involved in training LLMs and can speed up training considerably compared to CPUs. TPUs often come with large amounts of high-bandwidth memory, allowing for the handling of large models and batch sizes during training, which can lead to bet…

I assume that's a Gemini LLM response? You can tell Gemini is bullshitting when it starts using "often" or "usually" - like in this case "TPUs often come with large amounts of memory". Either they did or they didn't. "This (particular) mall often has a Starbucks" was one I encountered recently.

Re: Gemini 3.1 Pro

#467

Post by surgical_fire »

CamperBob2 wrote: post #349
surgical_fire wrote: post #146

Earlier quoted context omitted.

May be very silly of me, but I avoid using Gemini on my personal Google account. I use it at work, because my employer provides it. I am scared some automated system may just decide I am doing something bad and terminate my account. I have been moving important things to Proton, but there are some stuff that I couldn't change that would cause me a lot of annoyance. It's not trivial to set up an alternative account ju…

For what it's worth, there was an (unfortunately unsuccessful) HN submission from a guy who got his Gemini account banned, apparently without losing his whole Google account: https://news.ycombinator.com/item?id=47007906

Comforting to know that they may ban you from only some of their services, I guess?

I really regret relying so much on my Google account for so long. Untangling myself from it is really hard. Some places treat your email as a login, not as simply as a way to contact you. This is doubly concerning for government websites, where setting up a new account may just not be a possibility.

At some point I suppose Gemini will be the only viable option for LLMs, so oh well.

Re: Gemini 3.1 Pro

#468

Post by TZubiri »

small_model wrote: post #444
simonw wrote: post #332

Earlier quoted context omitted.

I had an interesting experience recently where I ran Opus 4.6 against a problem that o4-mini had previously convinced me wasn't tractable... and Opus 4.6 found me a great solution. https://github.com/simonw/sqlite-chronicle/issues/20 This inspired me to point the latest models at a bunch of my older projects, resulting in a flurry of fixes and unblocks.

I have a codebase (personal project) and every time there is a new Claude Opus model I get it to do a full code review. Never had any breakages in last couple of model updates. Worried one day it just generates a binary and deletes all the code.

No version control?

Re: Gemini 3.1 Pro

#469

Post by TZubiri »

agentifysh wrote: post #454
minimaxir wrote: post #23

Price is unchanged from Gemini 3 Pro: $2/M input, $12/M output. https://ai.google.dev/gemini-api/docs/pricing Knowledge cutoff is unchanged at Jan 2025. Gemini 3.1 Pro supports "medium" thinking where Gemini 3 did not: https://ai.google.dev/gemini-api/docs/gemini-3 Compare to Opus 4.6's $5/M input, $25/M output. If Gemini 3.1 Pro does indeed have similar performance, the price difference is notable.

Looks like its cheaper than codex ??? this might be interesting then

It's not trained for agentic coding I don't think

Re: Gemini 3.1 Pro

#470

Post by stephen_cagle »

spankalee wrote: post #199

I hope this works better than 3.0 Pro I'm a former Googler and know some people near the team, so I mildly root for them to at least do well, but Gemini is consistently the most frustrating model I've used for development. It's stunningly good at reasoning, design, and generating the raw code, but it just falls over a lot when actually trying to get things done, especially compared to Claude Opus. Within VS Code Copi…

I also worked at Google (on the original Gemini, when it was still Bard internally) and my experience largely mirrors this. My finding is that Gemini is pretty great for factual information and also it is the only one that I can reliably (even with the video camera) take a picture of a bird and have it tell me what the bird is. But it is just pretty bad as a model to help with development, myself and everyone I know uses Claude. The benchmarks are always really close, but my experience is that it does not translate to real world (mostly coding) task.

tldr; It is great at search, not so much action.

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